Data-intensive systems are a technological building block supporting Big Data and Data Science applications.This book familiarizes readers with core concepts that they should be aware of before continuing with independent work and the more advanced technical reference literature that dominates the current landscape.
The material in the book is structured following a problem-based approach. This means that the content in the chapters is focused on developing solutions to simplified, but still realistic problems using data-intensive technologies and approaches. The reader follows one reference scenario through the whole book, that uses an open Apache dataset.
The origins of this volume are in lectures from a master's course in Data-intensive Systems, given at the University of Stavanger. Some chapters were also a base for guest lectures at Purdue University and Lodz University of Technology.

Introduces students to core concepts before they continue with advanced technical literature Only strictly educational text on the market not tied to just one software framework Clear didactic approach following problems-based learning Balances data analysis and administrative aspects of data-intensive systems, ideal for a first course in the domain

Inhalt
Introduction.- Hadoop 101 and reference scenario.- Functional abstraction.- Introduction to MapReduce.- Hadoop Architecture.- MapReduce algorithms and patterns.- NOSQL Databases.- Spark.